A kit for massively parallel single cell gene expression analysis Abstract Interest in single cell gene expression analysis harnessing the capability of next- generation sequencing (NGS) has recently gained momentum in the academic community. Although sequencing has become cheaper, the ability to measure gene expression profile at the single cell level is extremely constrained by the limitation of technolog for preparing sequencing libraries from single cells. Currently available sample preparation techniques require expensive instruments and are brute-force and low-throughput. Single cell gene expression would be much more powerful if it can be scaled to examine tens of thousands of cells at a time and across many genes. Not only will such technology advance our knowledge in basic biology and medicine, it also has many potential clinical applications. We have recently developed a low-cost and high-resolution massively parallel method to prepare sequencing libraries from large number of single cells for gene expression analysis. The method is based on the concept of stochastic labeling, executed at the single cell and the single molecule level. We have successfully conducted expression analysis of ~100 genes of close to 1000 single cells per sample routinely, and have demonstrated the ability of our system to classify major cell types in heterogeneous cell mixtures such as human blood. The scalability, throughput, and economy of our technology far exceed existing commercial platforms. For this proposed Phase II project, we plan to further scale our technology to enable routine analysis of hundreds of genes across 10,000 cells per sample, and to convert the current working prototype into an exportable product that includes a reagent kit, a simple reagent-loading device, and supporting assay design and analysis software.